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Suboptimal Linear Distributed Control-Estimation Synthesis for Stochastic Multi-Agent System
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DOI：10.1109/ACCESS.2024.3449874.png)
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摘要
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This paper considers the distributed cooperative control problem for a linear stochastic multi-agent system (MAS). The optimal cooperative control design for each agent is challenging due to the limited neighboring information, contingent upon the MAS network topology. A synthesized distributed control-estimation framework is proposed to address the computationally tractable suboptimal solution. In particular, a distributed estimator extends MAS information beyond neighboring agents, allowing interactions with non-neighboring agents. The proposed control-estimation law is theoretically verified and further validated using numerical simulations.
Keyword:
Artificial neural networks
Decentralized control
Vectors
Multi-agent systems
Estimation
Costs
Network topology
Distributed control
optimal control
multi-agent systems
cooperative control
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
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